Transmission Network Congestion in Deregulated
Wholesale Electricity Market
N S Modi,
Member IEEE
, B R Parekh
∗Abstract—Electricity market plays an important role in improving the economics of electrical power system. Transmission network is vital entity in open access deregulated wholesale electricity market. Whenever transmission network congestion occurs in electricity market, it divides the market in different zones and the trading price of electricity will no longer remains the same for the whole system. Bidding strategies in electricity market, where by changing the bid, market player changes the revenue of every participant of the market. This paper, after present-ing a conceptual understandpresent-ing of electricity market, gives performance analysis of electricity market for a small three bus system. How network congestion segregates the wholesale electricity market and forces the market to change its price from a common market clearing price to locational market price has also been illustratively demonstrated. Concept of strategic bid-ding by the participant of the market and its effect on the revenue generation of the players has been com-puted and analyzed with revising the cost function of one of the generator.
Keywords: Power System Deregulation, Energy Auc-tion, Network CongesAuc-tion, Strategic Bidding
1
Introduction
The success of privatization of most of the industries led people to think for the deregulation of electric power system. This yields to restructuring of currently ver-tically integrated utility (VIU) to the main three util-ities, namely generation company (GENCO), transmis-sion company (TRANSCO) and distribution company (DISCO). The success in the energy privatization in the countries like UK, USA, Norway and Australia has en-couraged many more countries to privatize their electric-ity industry. India has also participated in the process and most of the states of India have restructured their electricity boards. Ever since the restructuring has taken palce, the electric power industry has seen tremendous changes in its operation and governance. Electricity, be-ing a concurrent entity, can not be stored easily. This
∗N. S. Modi is with Department of Electrical Engineering, G H
Patel College of Engineering & Technology, Vallabh Vidyanagar, Gujarat, India. Email: nileshsmodi@gmail.com
B. R. Parekh is Professor & Head at Department of Electrical Engi-neering, Birla Vishwakarma Mahavidyalaya - Engineering College, Vallabh Vidyanagar, Gujarat, India. Email: brp.bvm@gmail.com
emphasis on generation and consumption of electricity at the same moment of time. Ascertain of electricity mar-ket gave new dimension on power system engineer and the economics of power system.
In develop countries Electricity market is already func-tioning and it is being started to introduce in developing countries. The sole purpose of introduction of deregula-tion and electricity market is to create a healthy compe-tition among the participant of the market and to make electricity market more efficient, liquid and complete [1]. The fundamental objectives behind the establishment of electricity market are the secure operation of power sys-tem and facilitating an economic operation of the syssys-tem. Key entities of the electricity market are Generating companies (GENCOs), independent system operator (ISO) -many a times known as system operator (SO), Transmis-sion companies (TRANSCOs) and Distribution compa-nies (DISCOs) [2]. The development of electricity market also aims for the maximum participation from the electric utilities to provide transparent and non-discriminatory platform for energy producers.
The efficiency of market decreases in the event of trans-mission line congestion. The congestion results in price change and reduces the market efficiency. Congestion can be managed by different approaches. One of the approach is real and reactive power rescheduling [3]. Strategic bid-ding is the gaming of players of the market by which the players in the market submits bid to accomplish maxi-mum benefit.
2
Electricity Market
In almost every areas of technology, privatization has al-ways made a positive impact on the performance of the industry. In 1989, UK became one of the pioneer coun-try to unbundle their electricity induscoun-try [4]. After the success of deregulation in the UK, most of the countries of Europe have started to unbundle their vertically inte-grated utilities. The successes of these countries have en-couraged the other countries to privatize their electricity industry which includes Finland, Australia, New Zealand, Taiwan and Brazil. In India the unbundling procedure has been carried out by most of the states and there ex-ist a state regulatory commission in all states who has opted for deregulation of electricity industry. The devel-opment of electricity market in India is still at nascent stage.
One of the objective behind privatization of electricity industry is to introduce competition at every stage. This leads the engineer to develop a common place for trading electricity assets and this in turn develops the term elec-tricity market. Elecelec-tricity market is a place where trading of power takes place between power producers and con-sumers. Along with the trading of active power, trading of ancillary services can also been carry out in electricity market. The reforms of electricity has not only emerged electricity market but also increase the number of pri-vate players and radically changed the scenario of power system economics.
3
Electricity Market Architecture
The electricity market architecture comprises of main four entities namely GENCOs, TRANSOs, DISCOs and an independent system operator (ISO) [2]. GENCO is not necessary to have its own generating plants, but it can negotiate on behalf of generating companies. In an-cillary market GENCO has opportunity to sell its reserves and reactive power. The GENCO will try to maximize its own profit, whatever way it can, by selling the power in the market. TRANSCO transmit the power from power producer to power consumer. It also maintains the trans-mission system to increase overall reliability of power sys-tem. DISCO distributes the power to retail companies, brokers or to its own consumers. ISO is an independent body which maintains the instantaneous power balance in the system. ISO is also responsible for secure opera-tion of the grid. There could be two types of ISO, one is known as MinISO and the other is MaxISO [2]. While MinISO, look looking after the grid security and has no role in power market, MaxISO model includes power ex-change (PX). The function of power exex-change is to pro-vide a competitive market place for all the participant of the market. ISO uses the assets of TRANSCO for its functioning. The role of ISO also encompasses the fare use of transmission network, maximizing social welfare of
the market, running power exchange (PX), maintaining grid security and to run separate market for ancillary ser-vices. The calculation of system price and bid matching can be carried out by power exchange [2, 4].
The electricity market can be classified by the entity which it trades. The broader classification of electricity market includes power market, ancillary service market and transmission market. The classification can also be carried out by the operating mechanism of market, which leads to forward market, spot market and pool market. Sport market is also known as real time market [5]. The market can also be classified as wholesale market and re-tail market.
The price in this type market can be calculated by finding equilibrium point of the supply and demand curve. Fig. 1 illustrates this mechanism.
Figure 1: Market Equilibrium Point
The equilibrium point is known as market clearing price (MCP). The ISO or PX accepts bids from all the play-ers of the market and determines the MCP. Whenever there is no network congestion, MCP is the only one price for every node of the system. But because of the congestion the whole system is being segregated in dif-ferent zones and zonal market clearing price is used for different zones. This price is also known as locational marginal price (LMP). LMP can be understood as the cost of next MW of power at that particular node. The following section explains the network congestion and its consequences on market price.
4
Network Congestion
curtailment of loads. It can also be solved by remov-ing the overloaded component from the system. But this might aggregate the network congestion.
5
Strategic Bidding
In a pool electricity market every player, whether power producer or consumer, submit the bid. The PX collects all the bids and the MCP is declared for the operation of the market. Now if any players strategically bids then even at common MCP the player can gain profit. This is known as gaming in electricity market. It is also known as strategic bidding by the player to avail maximum benefit from the market. Under ideal market condition, power producers have every reason to bid on marginal cost of their generating plants [5]. The gaming can be played by withdrawing some portion of the operating capacity or by modifying the marginal cost or operating cost while bidding.
In this paper, gaming has been illustrated by modifying the cost function of the generator connected to bus B. By the strategic bidding the change in the social welfare is calculated and analyzed.
6
Example Power System
To illustrate congestion and bidding strategy in electric-ity market operation under deregulated environment a simple 3-bus system has been used. Fig. 2 shows the schematic of a loss less electric power system under study.
Figure 2: A Sample Power System
Both the generator have quadratic cost curve [4,8] and its operating limits are as showing in (1) and (2). The operating limits are inMW .
C(G1) = 0.012P12+ 10P1+ 250 INR/h;50≤P1≤500
(1)
C(G2) = 0.02P2
2+9P2+475 INR/h; 100≤P2≤700 (2)
where,P1 andP2 are the power generation by respective generators. The two loads have quadratic cost function and its operating limits are given by (3) and (4). The operating limits are inM W.
C(L1) =−0.018L2
1+ 30L1 INR/h;0≤L1≤900 (3)
C(L2) =−0.012L22+ 20L2 INR/h;0≤L2≤200 (4)
The loads are assumed to be elastic in nature so depend-ing upon the power offered from market; both the utilities will change its demand so as to obtain equilibrium point between received power and demand. The maximum op-erating capacity of each line is as show in Table 1.
Line Limit(M W) AB 100 AC 200 BC 400
Table 1: Operating Limits of Lines
Line AC and BC have same impedance and AB has impedance equals to twice of AC. It is assumed that bid offered by every utility in the market, whether the gen-erating utility or the utility which receives power from market, is on its marginal cost.
7
Unconstrained System
In the central auction type of market, all the suppliers and consumers will submit the bid to central pool or ex-change and market will decide the market clearing price (MCP) based on the equilibrium point of the bids. For the system shown in Fig. 2, with bidding function being the marginal cost, the market clearing price would come to 16.9552 INR/MWh. With this MCP the output of each generators and catered demand of each consumers is tabulated in Table 2.
The individual producer surplus is defined by (5).
Surplus= (M CP ×Pi)−C(Pi) wherei= 1,2, ..., n
(5) where, M CP ×Pi is known as revenue generated with
market clearing price andC(Pi) is known as revenue
Generator/ Price Quantity Surplus(Profit) Load (INR/hr) M W (INR/hr)
G1 16.9552 289.96 757.80 G2 16.9552 198.978 316.06 L1 16.9552 362.244 2363.4 L2 16.9552 126.70 193.41 Table 2: Market Clearing, Transmission Unconstrained
Surplus=C(Li)−(M CP×Li)wherei= 1,2, ..., n (6)
Where, M CP ×Li is known as payment with market
clearing price and C(Li) is known as actual benefits.
The social welfare of the market can be calculated by (7).
ψ=
n X
i=1
C(Li)− m X
i=1
C(Gi) (7)
In the unconstrained solution of the system, the social welfare is equal to 3613 INR/hr.
7.1
DC Power Flow [7]
However a full ac power is the accurate method to know the line loading of the system under study, DC power flow has been used throughout the work. While giving the idea of M W flows on transmission line, DC power flow solution does not give any indication of what happens to voltage magnitudes. With its usual notations, DC power can be solved with the following equations.
Pik= 1 xik
(θi−θk) (8)
Pi= n X
k=buses onnectedtoi
Pk (9)
The system has been solved for DC power flow and the loading of the lines is calculated. Table 3 gives the loading on each line.
Line M W
AB 22.74 AC 267.21 BC 221.71
Table 3: Line Flow, Transmission Unconstrained
8
Constrained System
It can be observed from the above analysis that, with this bidding and a common MCP leads to the network con-gestion for the system under study by overloading of line AC. To relieve the network from congestion, the above system has to be solved under transmission line capac-ity constraints. This will alter the output of generator (supplier) and the catered demand (consumer). Because of network congestion the MCP is not valid for all the nodes of the market and will lead to different locational marginal price (LMP) at each node. The results of con-strained DC power flow are as shown in Table 4.
Gen/ LMP Quantity Surplus(Profit) Load (INR/hr) M W (INR/hr)
G1 15.34 222.75 345.41 G2 14.27 131.36 -127.24 L1 18.89 308.46 1714.3 L2 18.89 46.03 25.66
Table 4: Market Clearing, Transmission Constrained It can be seen that the price on bus A is more than bus B as costly generator is attached to that bus. LoadL1and
L2 are connected to bus C so the LMP on that is bus is same forL1andL2.
The significant observation, the outcome of network con-gestion, is that the payment received by generator located on bus B is less than its production cost. It is under the loss in network congested electricity market. The social welfare has reduced to 3359 INR/hr.
The congestion rent is defined as the difference be-tween total demand charges and total generation pay-ment would come to 1397.3 INR/hr. This amount, which is revenue generation by Independent system operator, can be distributed to transmission companies.
There are number of ways to reduce the revenue loss of generator connected to bus B. One of them is to strate-gic bidding by generator (supplier). This is popularly known as gaming. The following analysis shows the gaming/strategic bidding done by supplier at bus B, by changing its linear portion of cost function from (2) to (10).
9
Strategic Bidding
The supplier (generator) connected to bus B, changes its cost function from (2) to (10).
C(G2) = 0.01P2
2 + 12P2+ 475 INR/h (10)
Generator/ Price Quantity Load (INR/MWh) (M W)
G1 16.6552 277.29 G2 16.6552 232.75 L1 16.6552 370.68 L2 16.6552 139.36
Table 5: Strategic Bidding, Transmission Unconstrained
The social welfare under unconstrained solution is 3602.56 INR/hr. Further by solving the network for con-gesting relief, we can get different LMP for every node.
Gen/ LMP Quantity Surplus(Profit) Load (INR/hr) M W (INR/hr)
G1 15.06 211.13 372.75 G2 15.33 166.69 70.64
L1 18.56 317.75 1817.6 L2 18.56 59.96 43.20
Table 6: Strategic Bidding, Transmission Constrained
It can be found that the social welfare is 3534.77 INR/hr and congestion rent is now 1230.68 INR/hr. More im-portantly, by strategic bidding by the supplier at bus B making profit as compared to loss previously.
10
Conclusion
In this paper, network congestion in deregulated electric-ity market has been illustrated and evaluated. The con-cept of game theory in the market has also been demon-strated illustratively. It has been show that how equilib-rium point of electricity market deviates under the strate-gic gaming. The analysis carried out revealed the fact that congestion will reduce the market efficiency and also the social welfare.
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N S Modi received his B. E. degree in Electrical Engi-neering and M.E. degree in Electrical EngiEngi-neering from Sadar Patel University in the year 2001 and 2004 respec-tively. He is currently working as Lecturer in Electrical Engineering at G H Patel College of Engineering & Tech-nology, Sardar Patel University, Vallabh Vidyanager, In-dia. His research interest includes power system oper-ation, simulation of electrical system, deregulation and electricity market. He is member of IEEE and life mem-ber of ISTE and Institute of Engineers (India).
